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Multisensor. Multisource Information fusion: architectures, algorithms, and applications 2003

This Volume 5099 of the conference proceedings contains 45 papers. Topics discussed include classification and decision fusion, image level fusion, approximate reasoning methodologies, estimation and tracking, fusion methodologies, evolving concepts and methodologies, architectures and related topics, industrial, medical and speech applications, defense applications, sensor/resource management and related topics.

关键词： sensor data fusion

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Technical Overview of the Sarnoff Acadia ii Vision Processor

Technical Overview of the Sarnoff Acadia II Vision Processor

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Conference on Multisensor, Multisource Information fusion - architectures, algorithms and applications 2010

作者： van der Wal, Gooitzen S. Sarnoff Corp Princeton NJ 08540 USA

ISBN: (纸本)9780819481740

The Sarnoff Acadia (R) ii is a powerful vision processing SoC (System-on-a-Chip) that was specifically developed to support advanced vision applications where system size, weight and/or power are severely constrained. This paper, targeted at vision system developers, presents a detailed technical overview of the Acadia (R) ii, highlighting its architecture, processing capabilities, memory and peripheral interfaces. All major subsystems will be covered, including: video preprocessing, specialized vision processing cores for multi-spectral image fusion, multi-resolution contrast normalization, noise coring, image warping, and motion estimation. Application processing via the MPCore (R), an integrated set of four ARM (R) 11 floating point processors with associated peripheral interfaces is presented in detail. The paper will emphasize the programmability of the Acadia (R) ii, while describing its ability to provide state-of-the-art real-time image processing in a small, power optimized package.*

关键词： Real-time Multiresolution Vision processing Image fusion Stabilization Embedded Processing Multicore multi-spectral

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Formal methods of automated reasoning for situational estimation

Formal methods of automated reasoning for situational estima...

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Conference on sensor fusion - architectures, algorithms, and applications

作者： Llinas, J SUNY/Buffalo (United States)

ISBN: (纸本)081942482X

Most research and prototype development of automated methods for situational estimation in the data fusion community have applied heuristic approaches coupled to techniques for uncertainty management. Reasoning theorists would label these methods as those of the parametric reasoning class. Such methods are reasonable when the so-called ''closed world'' assumption can be confidently applied (ability to full prespecify expected conditions) which might have been reasonable in the ''Soviet Era'' but would appear fragile/brittle for current-day application. Motivated in part by these considerations and by the need to consider much more cost-effective knowledge-based-system development in an era of declining budgets, this paper offers some discussion on the applicability of more formal methods of reasoning for KBS. It is concluded that strictly formal methods for real-world applications require yet further theoretical development but that movement toward formalization is possible.

关键词： automated reasoning data fusion information fusion formal methods truth maintenance default reasoning

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Estimation of subpixel-resolution motion fields from segmented image sequences

Estimation of subpixel-resolution motion fields from segment...

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Conference on sensor fusion - architectures, algorithms, and applications ii

作者： Schultz, RR Stevenson, RL Univ N Dakota Dept Elect Engn Grand Forks ND 58202 USA

ISBN: (纸本)0819428256

Super-resolution enhancement algorithms are used to estimate a high-resolution video still (HRVS) from several low-resolution frames, provided that objects within the image sequence move with subpixel increments. However, estimating an accurate subpixel-resolution motion field between two low-resolution, noisy video frames has proven to be a formidable challenge. Up-sampling the image sequence frames followed by the application of block matching, optical flow estimation, or Bayesian motion estimation results in relatively poor subpixel-resolution motion fields, and consequently inaccurate regions within the super-resolution enhanced video still. This is particularly true for large interpolation factors (greater than or equal to 4). To improve the quality of the subpixel motion fields and the corresponding HRVS, motion can be estimated for each object within a segmented image sequence. First, a reference video frame is segmented into its constituent objects, and a mask is generated for each object which describes its spatial location. As described previously, subpixel-resolution motion estimation is then conducted by video frame up-sampling followed by the application of a motion estimation algorithm. Finally, the motion vectors are averaged over the region of each mask by applying an a-trimmed mean filter to the horizontal and vertical components separately. Since each object moves as a single entity, averaging eliminates many of the motion estimation errors and results in much more consistent subpixel motion fields. A substantial improvement is also visible within particular regions of the HRVS estimates. Subpixel-resolution motion fields and HRVS estimates are computed for interpolation factors of 2, 4, 8, and 16, to examine the benefits of object segmentation and motion field averaging.

关键词： interpolation motion estimation segmentation sensor fusion super-resolution enhancement

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Three dimensional data fusion for biomedical surface reconstruction

Three dimensional data fusion for biomedical surface reconst...

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Conference on sensor fusion - architectures, algorithms, and applications

作者： Zachary, JM Iyengar, SS Louisiana State Univ. (United States)

ISBN: (纸本)081942482X

Traditional surface reconstruction techniques have focused exclusively on contour sections in one anatomical direction. However, in certain medical situations, such as in presurgical planning and radiation treatment, medical scans are taking of the patient in three orthogonal directions to better localize pathologies. fusion techniques must be used to register this data with respect to a surface fitting method. We explore the issues involved in fusing data from ellipsoid anatomy, such as the brain, heart, and major organs. The output of the fusion process is a set of data points which are correlated to one another to represent the surface of a single object. This data network is then used as input to a surface fitting algorithm which depends on two sampling metrics which we derive. The solution to this problem is important in presurgical planning, radiation treatment, and telemedical systems.

关键词： data fusion contour reconstruction surface reconstruction scattered data

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The system parameter fusion principle and its application to fuzzy pattern recognition

The system parameter fusion principle and its application to...

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Conference on Multisensor, Multisource Information fusion - architectures, algorithms and applications 2003

作者： Pu, QG Univ Sci & Technol Ctr Comp Suzhou 215011 Jiangsu Peoples R China

ISBN: (纸本)0819449598

Modern technology provides a great amount of information. In computer monitoring systems or computer control systems, especially real-time expert systems, in order to have the situation in hand, we need one or two parameters to express the quality and/or security of the whole system. This paper presents a principle for synthesizing measurements of multiple system parameters into a single parameter and its application to fuzzy pattern recognition.

关键词： sensor fusion fuzzy pattern recognition computer monitoring systems computer control systems realtime expert systems

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MathWeb: a concurrent image analysis tool suite for multi-spectral data fusion

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Proceedings of SPIE - The International Society for Optical Engineering 1999年 3719卷 351-358页

作者： Achalakul, Tiranee Haaland, Peter D. Taylor, Stephen Syracuse Univ Syracuse United States

This paper describes a preliminary approach to the fusion of multi-spectral image data for the analysis of cervical cancer. The long-term goal of this research is to define spectral signatures and automatically detect cancer cell structures. The approach combines a multi-spectral microscope with an image analysis tool suite, MathWeb. The tool suite incorporates a concurrent Principal Component Transform (PCT) that is used to fuse the multi-spectral data. This paper describes the general approach and the concurrent PCT algorithm. The algorithm is evaluated from both the perspective of image quality and performance scalability.

关键词： Image analysis

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IMAGE-BASED TARGET TRACKING - fusion ARCHITECTURE AND sensor MANAGEMENT 2

IMAGE-BASED TARGET TRACKING - FUSION ARCHITECTURE AND SENSOR...

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CONF ON SIGNAL PROCESSING, sensor fusion, AND TARGET RECOGNITION 2

作者： HERSEN, B LALO, A LANEUVILLE, D MARITON, M MATRA MS2i (France)

ISBN: (纸本)0819411914

Following the acceptance of the linear Gauss Markov paradigm pioneered by Kalman, the engineering practice for the design of target tracking applications had been maturing over the last two decades. In recent years however two emerging facts have called for a renewed attention from the research community: (1) the generalization of multiple sensor architectures, motivated by higher requirements in terms of target description and robustness to electronic warfare, and (2) the availability of affordable imaging sensors, following progress in infrared detectors technology. The purpose of this communication is to report on some recent work addressing the issues raised by these two new aspects of tracking application design. Ideas are illustrated using an air defense scenario.

关键词： sensors Optical sensors Detection and tracking algorithms Environmental sensing Image processing Defense and security Image fusion Image sensors Imaging systems sensor fusion

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Better-than-the-Best fusion Algorithm with Application in Human Activity Recognition

Better-than-the-Best Fusion Algorithm with Application in Hu...

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Conference on Multisensor, Multisource Information fusion - architectures, algorithms, and applications

作者： Najjar, Nayeff Gupta, Shalabh Univ Connecticut Storrs CT 06269 USA

ISBN: (纸本)9781628416145

This paper introduces the Better-than-the-Best fusion (BB-Fus) algorithm. The BB-Fus algorithm is a simple and effective information fusion algorithm that combines the information from different sources (be it sensors, features or classifiers) to improve the Correct Classification Rate (CCR). It can be observed that in most classification problems, different sensors or features might have different classification accuracies in separating different classes. Therefore, this paper constructs an optimal decision tree that isolates one class at a time with the best sensor to separate that particular class. The paper shows that the decision tree improves the overall CCR as compared to the use of any single sensor or feature for any 3-class classification problem. The efficiency of the BB-Fus algorithm is validated on the Opportunity data set to solve the human activity recognition problem where a set of 56 sensors (including a localization system, accelerometers, inertial measurement units and magnetic sensors mounted on various body parts;besides, accelerometers and gyroscopes mounted on different objects) are used. The CCR resulting from the BB-Fus algorithm is 96% while the best sensor achieved 94% CCR.

关键词： sensor fusion Information fusion Human Activity Recognition BB-Fus Decision Trees

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ELIPS: toward a sensor fusion processor on a chip

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Proceedings of SPIE - The International Society for Optical Engineering 1999年 3719卷 209-219页

作者： Daud, Taher Stoica, Adrian Thomas, Tyson Li, Wei-te Fabunmi, James California Inst of Technology Pasadena United States

The paper presents the concept and initial tests from the hardware implementation of a low-power, high-speed reconfigurable sensor fusion processor. The Extended Logic Intelligent Processing System (ELIPS) processor is developed to seamlessly combine rule-based systems, fuzzy logic, and neural networks to achieve parallel fusion of sensor in compact low power VLSI. The first demonstration of the ELIPS concept targets interceptor functionality; other applications, mainly in robotics and autonomous systems are considered for the future. The main assumption behind ELIPS is that fuzzy, rule-based and neural forms of computation can serve as the main primitives of an 'intelligent' processor. Thus, in the same way classic processors are designed to optimize the hardware implementation of a set of fundamental operations, ELIPS is developed as an efficient implementation of computational intelligence primitives, and relies on a set of fuzzy set, fuzzy inference and neural modules, built in programmable analog hardware. The hardware programmability allows the processor to reconfigure into different machines, taking the most efficient hardware implementation during each phase of information processing. Following software demonstrations on several interceptor data, three important ELIPS building blocks (a fuzzy set preprocessor, a rule-based fuzzy system and a neural network) have been fabricated in analog VLSI hardware and demonstrated microsecond-processing times.

关键词： Computer hardware

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